A critical review of using the Peukert equation for determining the remaining capacity of lead-acid and lithium-ion batteries

In many applications it is essential to predict the remaining capacity of a battery reliably, accurately and simply. Several existing techniques for predicting the remaining capacity of a lead-acid battery discharged with a variable current are based on variants of Peukert's empirical equation, which relates the available capacity to a constant discharge current. This paper presents a critical review of these techniques in the light of experimental tests that were carried out on two lead-acid commercial batteries. The relevance of these Peukert's equation based techniques to lithium-ion batteries is also discussed in the light of tests carried on a lithium-ion power battery. The basic conclusion of the paper is that Peukert's equation cannot be used to predict the state of charge of a battery accurately unless it is discharged at a constant current and constant temperature.     

UAV image stitching by estimating orthograph with RGB cameras

In the field of image stitching, cases with large camera optical center movement and large parallax have been the virgin territory of research. The goal of image stitching is to overcome the parallax and stitch a natural image. We look into this problem in the context of ultra-low altitude flight of a UAV. We model the 3D world in this scenario and quickly estimate orthographic projection by pairs of homography matrices. Our stitching method can achieve precise alignment since it takes parallax well into consideration. The stitching results are natural and the extra time consumed is short.     

Particles and grid

In this paper, hybrid methods involving particles have been investigated. First, the main characteristics of the particle method are briefly outlined and an example of application to a really complex case is presented. The particle/grid method which is also the basis for mixing particles with other methods is described. The two main alternatives: domain decomposition and perturbation formulation are then discussed and some examples are presented.     

基于多域特征的螺栓松动检测方法研究

螺栓作为机械设备最常用的连接件,螺栓连接的稳定性对保障机械设备安全运行起着至关重要的作用,对螺栓松动程度进行检测有着重要意义。针对螺栓松动4种不同状态,提出了一种基于变分模态分解(VMD)及时频敏感特征与最小二乘支持向量机(LSSVM)相结合的螺栓松动检测方法。针对螺栓松动的4种不同状态,搭建了螺栓松动检测模拟实验平台,通过加速度传感器获取螺栓松动4种不同状态振动响应数据;提取了时频域敏感特征量,结合VMD分解的IMF分量能量熵组成状态检测敏感多特征向量,将提取的多特征向量结合LSSVM对螺栓不同松动状态进行识别,并对比基于经验模态分解(EMD)-LSSVM及EMD-多特征-LSSVM检测结果。结果显示,基于多域特征的螺栓松动检测方法识别率优于EMD-LSSVM检测方法。